//
//  OpenAIAPI.swift
//  OpenAI API Implementation
//

import Foundation

/// OpenAI API helper for vision analysis
class OpenAIAPI {
    private let apiKey: String
    private let apiURL: URL
    private let model: String
    private let session: URLSession

    init(apiKey: String, model: String = "gpt-5.2-2025-12-11") {
        self.apiKey = apiKey
        self.apiURL = URL(string: "https://api.openai.com/v1/chat/completions")!
        self.model = model

        // Use .default instead of .ephemeral so TLS session tickets are cached.
        // Ephemeral sessions do a full TLS handshake on every request, which causes
        // transient -1200 (errSSLPeerHandshakeFail) errors with large image payloads.
        // Disable URL/cookie caching to avoid storing responses or credentials on disk.
        let config = URLSessionConfiguration.default
        config.timeoutIntervalForRequest = 120
        config.timeoutIntervalForResource = 300
        config.waitsForConnectivity = true
        config.urlCache = nil
        config.httpCookieStorage = nil
        self.session = URLSession(configuration: config)

        // Fire a lightweight HEAD request in the background to pre-establish the TLS
        // connection. This caches the TLS session ticket so the first real API call
        // (which carries a large image payload) doesn't need a cold TLS handshake.
        warmUpTLSConnection()
    }

    /// Sends a no-op HEAD request to the API host to establish and cache a TLS session.
    /// Failures are silently ignored — this is purely an optimization.
    private func warmUpTLSConnection() {
        var warmupRequest = URLRequest(url: apiURL)
        warmupRequest.httpMethod = "HEAD"
        warmupRequest.timeoutInterval = 10
        session.dataTask(with: warmupRequest) { _, _, _ in
            // Response doesn't matter — the TLS handshake is the goal
        }.resume()
    }

    /// Send a vision request to OpenAI with one or more labeled images.
    func analyzeImage(
        images: [(data: Data, label: String)],
        systemPrompt: String,
        conversationHistory: [(userPlaceholder: String, assistantResponse: String)] = [],
        userPrompt: String
    ) async throws -> (text: String, duration: TimeInterval) {
        let startTime = Date()

        // Build request
        var request = URLRequest(url: apiURL)
        request.httpMethod = "POST"
        request.timeoutInterval = 120
        request.setValue("Bearer \(apiKey)", forHTTPHeaderField: "Authorization")
        request.setValue("application/json", forHTTPHeaderField: "Content-Type")

        // Build messages array
        var messages: [[String: Any]] = []

        // Add system message first
        messages.append([
            "role": "system",
            "content": systemPrompt
        ])

        // Add conversation history
        for (userPlaceholder, assistantResponse) in conversationHistory {
            messages.append(["role": "user", "content": userPlaceholder])
            messages.append(["role": "assistant", "content": assistantResponse])
        }

        // Build current message with all labeled images + prompt
        var contentBlocks: [[String: Any]] = []
        for image in images {
            contentBlocks.append([
                "type": "text",
                "text": image.label
            ])
            contentBlocks.append([
                "type": "image_url",
                "image_url": [
                    "url": "data:image/jpeg;base64,\(image.data.base64EncodedString())"
                ]
            ])
        }
        contentBlocks.append([
            "type": "text",
            "text": userPrompt
        ])
        messages.append(["role": "user", "content": contentBlocks])

        // Build request body
        let body: [String: Any] = [
            "model": model,
            // `max_tokens` is deprecated/incompatible for some newer OpenAI models.
            "max_completion_tokens": 600,
            "messages": messages
        ]

        let bodyData = try JSONSerialization.data(withJSONObject: body)
        request.httpBody = bodyData
        let payloadMB = Double(bodyData.count) / 1_048_576.0
        print("🌐 OpenAI request: \(String(format: "%.1f", payloadMB))MB, \(images.count) image(s)")

        // Send request
        let (data, response) = try await session.data(for: request)

        guard let httpResponse = response as? HTTPURLResponse,
              (200...299).contains(httpResponse.statusCode) else {
            let responseString = String(data: data, encoding: .utf8) ?? "Unknown error"
            throw NSError(
                domain: "OpenAIAPI",
                code: (response as? HTTPURLResponse)?.statusCode ?? -1,
                userInfo: [NSLocalizedDescriptionKey: "API Error: \(responseString)"]
            )
        }

        // Parse response
        let json = try JSONSerialization.jsonObject(with: data) as? [String: Any]
        guard let choices = json?["choices"] as? [[String: Any]],
              let firstChoice = choices.first,
              let message = firstChoice["message"] as? [String: Any],
              let text = message["content"] as? String else {
            throw NSError(
                domain: "OpenAIAPI",
                code: -1,
                userInfo: [NSLocalizedDescriptionKey: "Invalid response format"]
            )
        }

        let duration = Date().timeIntervalSince(startTime)
        return (text: text, duration: duration)
    }
}